Triple
T22965137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Grand Crible dans la Théorie Analytique des Nombres |
E571018
|
entity |
| Predicate | appliesMethod |
P859
|
FINISHED |
| Object | large sieve |
—
|
NE NERFINISHED |
How this triple was built (3 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: large sieve | Statement: [Le Grand Crible dans la Théorie Analytique des Nombres, appliesMethod, large sieve]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: large sieve Context triple: [Le Grand Crible dans la Théorie Analytique des Nombres, appliesMethod, large sieve]
-
A.
Selberg sieve
The Selberg sieve is a powerful analytic number theory method developed by Atle Selberg for estimating the size of sets of integers filtered by divisibility conditions, particularly in the study of prime numbers.
-
B.
Brun sieve
The Brun sieve is a combinatorial method in analytic number theory, developed by Viggo Brun, used to estimate the distribution of prime numbers and almost-primes in various sequences.
-
C.
Brun combinatorial sieve
The Brun combinatorial sieve is a classical number-theoretic sieving method, developed by Viggo Brun, that uses combinatorial techniques to estimate the distribution of integers free of small prime factors and was historically applied to problems like twin primes.
-
D.
Siegel–Walfisz theorem
The Siegel–Walfisz theorem is a result in analytic number theory that gives strong uniform estimates for the distribution of prime numbers in arithmetic progressions with relatively small moduli.
-
E.
Hardy–Littlewood circle method
The Hardy–Littlewood circle method is a powerful analytic number theory technique that uses complex analysis and Fourier series to study additive problems such as Waring’s problem and the Goldbach conjecture.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: large sieve Target entity description: The large sieve is a powerful analytic number theory technique that provides upper bounds for the distribution of sequences in arithmetic progressions and related sieve problems.
-
A.
Selberg sieve
The Selberg sieve is a powerful analytic number theory method developed by Atle Selberg for estimating the size of sets of integers filtered by divisibility conditions, particularly in the study of prime numbers.
-
B.
Brun sieve
The Brun sieve is a combinatorial method in analytic number theory, developed by Viggo Brun, used to estimate the distribution of prime numbers and almost-primes in various sequences.
-
C.
Brun combinatorial sieve
The Brun combinatorial sieve is a classical number-theoretic sieving method, developed by Viggo Brun, that uses combinatorial techniques to estimate the distribution of integers free of small prime factors and was historically applied to problems like twin primes.
-
D.
Siegel–Walfisz theorem
The Siegel–Walfisz theorem is a result in analytic number theory that gives strong uniform estimates for the distribution of prime numbers in arithmetic progressions with relatively small moduli.
-
E.
Hardy–Littlewood circle method
The Hardy–Littlewood circle method is a powerful analytic number theory technique that uses complex analysis and Fourier series to study additive problems such as Waring’s problem and the Goldbach conjecture.
- F. None of above. chosen
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181f763688190aab8f444a1a71577 |
completed | April 29, 2026, 3:58 a.m. |
Created at: April 17, 2026, 3:47 p.m.